Robust Fault Isolation With Statistical Uncertainty in Identified Parameters

• Published in: IEEE transactions on signal processing Vol. 60; no. 10; pp. 5556 - 5561
• Main Authors: Jianfei Dong, Verhaegen, M., Gustafsson, F.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Additive faults; Additives; Applied sciences; Automatic control; Closed-form solution; Covariance matrix; Detection, estimation, filtering, equalization, prediction; Error detection; Exact sciences and technology; Fault isolation; Faults; Information technology; Information, signal and communications theory; Informationsteknik; Mathematical models; Parameter uncertainty; Reglerteknik; Representations; Robustness; Sensors; Signal and communications theory; Signal processing; Signal, noise; Statistical analysis; TECHNOLOGY; TEKNIKVETENSKAP; Telecommunications and information theory; Transaction processing; Uncertainty; Vectors; Error estimation; Measurement sensor; Robust estimation; Closed form equation; Additive faults; closed-form solution; Failures; fault isolation; Statistical method; Residual impurity; Defect localization; parameter uncertainty; Signal processing; statistical analysis; Defect detection
• ISSN: 1053-587X; 1941-0476; 1941-0476
• DOI: 10.1109/TSP.2012.2208639

This correspondence is a companion paper to [J. Dong, M. Verhaegen, and F. Gustafsson, "Robust Fault Detection With Statistical Uncertainty in Identified Parameters," IEEE Trans. Signal Process., vol. 60, no. 10, Oct. 2012], extending it to fault isolation. Also, here, use is made of a linear in the parameters model representation of the input-output behavior of the nominal system (i.e. fault-free). The projection of the residual onto directions only sensitive to individual faults is robustified against the stochastic errors of the estimated model parameters. The correspondence considers additive error sequences to the input and output quantities that represent failures like drift, biased, stuck, or saturated sensors/actuators.